Description

  Acquire basic skills in multivariate statistics and know how to visualize and analyze High-dimensional data.

Compétences visées

• Interpret and understand regression models
• Understand the multiple testing problem and be familiar with the Bonferroni method and the Benjamini-Hochberg procedure
• Understand the different features of the high dimension reduction techniques : Principal Component Analysis (PCA), Multidimensional Scaling (MDS), Stochastic Neighbour Embedding (SNE)
• Understand clustering methods of High-dimensional data such as : K-means, Agglomerative clustering (dendogram)

Bibliographie

Susan Holmes, Wolfgang Huber. Modern Statistics for Modern Biology. http://web.stanford.edu/class/bios221/book/

Contacts

Responsable(s) de l'enseignement

• Nicodeme Paul